MCP-server exposing ML models for prediction of kpoints distance / kpoints grid for SCF DFT calculations trained on QE data for 3D crystalline inorganic materials
Goldilocks MCP server
Provides k-point generation tools for Quantum ESPRESSO with SSSP1.3 PBEsol efficiency version of pseudo-potentials
Tools exposed:
estimate_kpoint_distance
Requires specification path to the structure file, confidence level (models are trained for levels 0.85,0.9, and 0.95), and the model (ALIGNN or RF)
Example prompt: "Can you please generate k-points spacing for structure 'path/to/BaGa4.cif', confidence level 0.95 with ALIGNN model?"
Outputs the predicted k-spacing, and the confidence interval
generate_kpoint_grid
Requires specification path to the structure file, confidence level (models are trained for levels 0.85,0.9, and 0.95), and the model (ALIGNN or RF)
Example prompt: "Can you please generate k-points grid for structure 'path/to/BaGa4.cif', confidence level 0.95 with ALIGNN model?"
Outputs the predicted kmesh, generated using the lower bound of k-spacing interval (to make sure that the probability that predicted value is in agreement with confidence level)
Installing MCP-server locally
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Install uv (https://docs.astral.sh/uv/getting-started/installation/)
-
Clone repository
git clone https://github.com/stfc/goldilocks-mcp.git
cd goldilocks-mcp
- Create virtual environment and install dependencies
uv venv --python 3.11
source .venv/bin/activate
uv pip install -e .
- Install pytorch-geometric (can't be installed from pyproject.toml but is required). See details https://pytorch-geometric.readthedocs.io/en/latest/install/installation.html
uv pip install pyg_lib torch_scatter torch_sparse torch_cluster torch_spline_conv -f https://data.pyg.org/whl/torch-2.8.0+cpu.html
uv pip install torch_geometric
Adding mcp to Claude Desktop
To add goldilocks-mcp to Claude Desktop:
-
Open or create the Claude Desktop configuration file:
- macOS/Linux:
~/Library/Application Support/Claude/claude_desktop_config.json - Windows: See instructions at https://modelcontextprotocol.io/docs/develop/build-server
- macOS/Linux:
-
If the file doesn't exist, create it with the content from
claude_desktop_config.json. If it already exists, merge thegoldilocks-mcpentry into the existingmcpServersobject. -
Important: Update the path in the config file. Replace
"absolute/path/to/goldilocks-mcp/goldilocks_mcp/"with the actual absolute path to thegoldilocks_mcpdirectory in your cloned repository.